ABSTRACT Pulmonary hypertension (PH) is a complex disorder associated with elevated pulmonary arterial pressure. Unlike systemic hypertension, PH is difficult to detect in routine physical examinations and the current gold standard for diagnosing PH is through invasive right heart catheterization. Unlike in systemic hypertension, for which patients have effective pharmacological management of blood pressure for decades, PH prognosis remains poor with 15% mortality within 1 year on modern therapy. Challenges in early detection of PH, as well as structural differences in the cardio-pulmonary system (e.g., thinner ventricular wall, more distributed compliance and larger number of peripheral vessels) may explain the stark differences in clinical outcomes between systemic hypertension and PH. Our current understanding of PH has largely been obtained through animal models, clinical studies and computational modeling. However, surgical banding or chronic hypoxia animal models do not fully reproduce the etiology of human PH. Invasive clinical measurements of pulmonary vascular resistance (PVR), stiffness and ventricular elastance provide limited insight into disease progression. Computational models have been developed to study growth and remodeling (G&R) in the ventricles and hemodynamics in PH. However, these models are incomplete: ventricular G&R models lack coupling with evolving pulmonary hemodynamics, whereas pulmonary hemodynamic models have not included ventricular-arterial coupling. Given that the interactions between RV and the pulmonary vasculature are a key determinant of the clinical course of PH, specifically, the transition from compensated to decompensated remodeling, we submit that there is a pressing need to develop a multi-scale (MS) computational model that can couple the short term (e.g. hemodynamics) and long-term G&R interactions between the RV and the pulmonary circulation. In this project, we propose to develop a multi-scale, multi-physics computational model of the cardio-pulmonary circulation and calibrate it using longitudinal data acquired on cohorts of pediatric pulmonary hypertension and control (e.g., cardiac transplant) subjects. The model will be the first of its kind because it will be able to describe the bi-directional interactions between evolving ventricular and vascular biomechanics and hemodynamics using human pulmonary hypertension data.